Overview

Dataset statistics

Number of variables11
Number of observations5695
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory533.9 KiB
Average record size in memory96.0 B

Variable types

Numeric11

Alerts

basket_size is highly overall correlated with distinct_stock_code and 3 other fieldsHigh correlation
distinct_stock_code is highly overall correlated with basket_size and 4 other fieldsHigh correlation
frequency is highly overall correlated with total_products and 1 other fieldsHigh correlation
recency is highly overall correlated with total_purchasesHigh correlation
returned is highly overall correlated with total_purchasesHigh correlation
revenue is highly overall correlated with basket_size and 3 other fieldsHigh correlation
total_products is highly overall correlated with basket_size and 4 other fieldsHigh correlation
total_purchases is highly overall correlated with distinct_stock_code and 5 other fieldsHigh correlation
unique_basket_size is highly overall correlated with basket_size and 1 other fieldsHigh correlation
revenue is highly skewed (γ1 = 22.58583907)Skewed
total_products is highly skewed (γ1 = 24.0961482)Skewed
basket_size is highly skewed (γ1 = 58.35463213)Skewed
avg_ticket is highly skewed (γ1 = 71.30305302)Skewed
returned is highly skewed (γ1 = 71.05769911)Skewed
customer_id has unique valuesUnique
returned has 4191 (73.6%) zerosZeros

Reproduction

Analysis started2024-07-01 14:11:27.871934
Analysis finished2024-07-01 14:12:09.620232
Duration41.75 seconds
Software versionydata-profiling v4.8.3
Download configurationconfig.json

Variables

customer_id
Real number (ℝ)

UNIQUE 

Distinct5695
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16600.599
Minimum12346
Maximum22709
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size89.0 KiB
2024-07-01T14:12:09.944273image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum12346
5-th percentile12699.1
Q114288.5
median16227
Q318210.5
95-th percentile21731.1
Maximum22709
Range10363
Interquartile range (IQR)3922

Descriptive statistics

Standard deviation2808.2419
Coefficient of variation (CV)0.16916509
Kurtosis-0.82111592
Mean16600.599
Median Absolute Deviation (MAD)1963
Skewness0.44127055
Sum94540411
Variance7886222.5
MonotonicityNot monotonic
2024-07-01T14:12:10.404524image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
17850 1
 
< 0.1%
21110 1
 
< 0.1%
13745 1
 
< 0.1%
15584 1
 
< 0.1%
21089 1
 
< 0.1%
21088 1
 
< 0.1%
21087 1
 
< 0.1%
21086 1
 
< 0.1%
15578 1
 
< 0.1%
12424 1
 
< 0.1%
Other values (5685) 5685
99.8%
ValueCountFrequency (%)
12346 1
< 0.1%
12347 1
< 0.1%
12348 1
< 0.1%
12349 1
< 0.1%
12350 1
< 0.1%
12352 1
< 0.1%
12353 1
< 0.1%
12354 1
< 0.1%
12355 1
< 0.1%
12356 1
< 0.1%
ValueCountFrequency (%)
22709 1
< 0.1%
22708 1
< 0.1%
22707 1
< 0.1%
22706 1
< 0.1%
22705 1
< 0.1%
22704 1
< 0.1%
22700 1
< 0.1%
22699 1
< 0.1%
22696 1
< 0.1%
22695 1
< 0.1%

revenue
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct5449
Distinct (%)95.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1774.2431
Minimum0.42
Maximum279138.02
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size89.0 KiB
2024-07-01T14:12:10.715593image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0.42
5-th percentile13.171
Q1236.135
median613.2
Q31570.74
95-th percentile5309.696
Maximum279138.02
Range279137.6
Interquartile range (IQR)1334.605

Descriptive statistics

Standard deviation7582.1085
Coefficient of variation (CV)4.2734328
Kurtosis675.64312
Mean1774.2431
Median Absolute Deviation (MAD)479.19
Skewness22.585839
Sum10104314
Variance57488370
MonotonicityNot monotonic
2024-07-01T14:12:10.993401image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7.95 9
 
0.2%
2.95 8
 
0.1%
4.95 8
 
0.1%
1.25 8
 
0.1%
3.75 7
 
0.1%
12.75 7
 
0.1%
1.65 7
 
0.1%
5.95 6
 
0.1%
7.5 6
 
0.1%
4.25 6
 
0.1%
Other values (5439) 5623
98.7%
ValueCountFrequency (%)
0.42 1
 
< 0.1%
0.65 1
 
< 0.1%
0.79 1
 
< 0.1%
0.84 4
0.1%
0.85 3
 
0.1%
1.07 1
 
< 0.1%
1.25 8
0.1%
1.44 1
 
< 0.1%
1.65 7
0.1%
1.69 1
 
< 0.1%
ValueCountFrequency (%)
279138.02 1
< 0.1%
259657.3 1
< 0.1%
194550.79 1
< 0.1%
140438.72 1
< 0.1%
124564.53 1
< 0.1%
117375.63 1
< 0.1%
91062.38 1
< 0.1%
77183.6 1
< 0.1%
72882.09 1
< 0.1%
66653.56 1
< 0.1%

recency
Real number (ℝ)

HIGH CORRELATION 

Distinct304
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean116.92818
Minimum0
Maximum373
Zeros37
Zeros (%)0.6%
Negative0
Negative (%)0.0%
Memory size89.0 KiB
2024-07-01T14:12:11.293693image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3
Q123
median71
Q3200
95-th percentile338
Maximum373
Range373
Interquartile range (IQR)177

Descriptive statistics

Standard deviation111.64589
Coefficient of variation (CV)0.95482451
Kurtosis-0.64261503
Mean116.92818
Median Absolute Deviation (MAD)61
Skewness0.81432182
Sum665906
Variance12464.806
MonotonicityNot monotonic
2024-07-01T14:12:11.586189image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 110
 
1.9%
4 105
 
1.8%
3 98
 
1.7%
2 92
 
1.6%
10 86
 
1.5%
8 82
 
1.4%
17 79
 
1.4%
9 79
 
1.4%
7 78
 
1.4%
15 66
 
1.2%
Other values (294) 4820
84.6%
ValueCountFrequency (%)
0 37
 
0.6%
1 110
1.9%
2 92
1.6%
3 98
1.7%
4 105
1.8%
5 52
0.9%
7 78
1.4%
8 82
1.4%
9 79
1.4%
10 86
1.5%
ValueCountFrequency (%)
373 23
0.4%
372 23
0.4%
371 17
0.3%
369 4
 
0.1%
368 13
0.2%
367 16
0.3%
366 15
0.3%
365 19
0.3%
364 11
0.2%
362 7
 
0.1%

total_products
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct1839
Distinct (%)32.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean962.91572
Minimum1
Maximum196844
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size89.0 KiB
2024-07-01T14:12:11.916320image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4
Q1106
median316
Q3800.5
95-th percentile2931.8
Maximum196844
Range196843
Interquartile range (IQR)694.5

Descriptive statistics

Standard deviation4296.7457
Coefficient of variation (CV)4.4622241
Kurtosis865.58334
Mean962.91572
Median Absolute Deviation (MAD)252
Skewness24.096148
Sum5483805
Variance18462023
MonotonicityNot monotonic
2024-07-01T14:12:12.238760image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 114
 
2.0%
2 73
 
1.3%
3 51
 
0.9%
4 49
 
0.9%
5 35
 
0.6%
6 29
 
0.5%
12 25
 
0.4%
88 22
 
0.4%
72 21
 
0.4%
7 20
 
0.4%
Other values (1829) 5256
92.3%
ValueCountFrequency (%)
1 114
2.0%
2 73
1.3%
3 51
0.9%
4 49
0.9%
5 35
 
0.6%
6 29
 
0.5%
7 20
 
0.4%
8 18
 
0.3%
9 7
 
0.1%
10 17
 
0.3%
ValueCountFrequency (%)
196844 1
< 0.1%
79963 1
< 0.1%
77373 1
< 0.1%
74215 1
< 0.1%
69993 1
< 0.1%
64549 1
< 0.1%
64124 1
< 0.1%
62812 1
< 0.1%
58243 1
< 0.1%
57785 1
< 0.1%

distinct_stock_code
Real number (ℝ)

HIGH CORRELATION 

Distinct528
Distinct (%)9.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean92.597893
Minimum1
Maximum7837
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size89.0 KiB
2024-07-01T14:12:12.561894image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q114
median41
Q3106
95-th percentile332.3
Maximum7837
Range7836
Interquartile range (IQR)92

Descriptive statistics

Standard deviation210.54112
Coefficient of variation (CV)2.273714
Kurtosis510.2114
Mean92.597893
Median Absolute Deviation (MAD)33
Skewness17.750592
Sum527345
Variance44327.564
MonotonicityNot monotonic
2024-07-01T14:12:12.895742image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 256
 
4.5%
2 149
 
2.6%
3 108
 
1.9%
10 100
 
1.8%
6 99
 
1.7%
9 93
 
1.6%
5 90
 
1.6%
4 88
 
1.5%
11 83
 
1.5%
7 83
 
1.5%
Other values (518) 4546
79.8%
ValueCountFrequency (%)
1 256
4.5%
2 149
2.6%
3 108
1.9%
4 88
 
1.5%
5 90
 
1.6%
6 99
 
1.7%
7 83
 
1.5%
8 81
 
1.4%
9 93
 
1.6%
10 100
 
1.8%
ValueCountFrequency (%)
7837 1
< 0.1%
5670 1
< 0.1%
5095 1
< 0.1%
4577 1
< 0.1%
2698 1
< 0.1%
2379 1
< 0.1%
2060 1
< 0.1%
1818 1
< 0.1%
1673 1
< 0.1%
1636 1
< 0.1%

total_purchases
Real number (ℝ)

HIGH CORRELATION 

Distinct56
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.471115
Minimum1
Maximum206
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size89.0 KiB
2024-07-01T14:12:13.215945image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q34
95-th percentile11
Maximum206
Range205
Interquartile range (IQR)3

Descriptive statistics

Standard deviation6.8133193
Coefficient of variation (CV)1.9628619
Kurtosis302.0876
Mean3.471115
Median Absolute Deviation (MAD)0
Skewness13.192713
Sum19768
Variance46.42132
MonotonicityNot monotonic
2024-07-01T14:12:14.337455image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 2871
50.4%
2 826
 
14.5%
3 502
 
8.8%
4 394
 
6.9%
5 237
 
4.2%
6 173
 
3.0%
7 138
 
2.4%
8 98
 
1.7%
9 69
 
1.2%
10 55
 
1.0%
Other values (46) 332
 
5.8%
ValueCountFrequency (%)
1 2871
50.4%
2 826
 
14.5%
3 502
 
8.8%
4 394
 
6.9%
5 237
 
4.2%
6 173
 
3.0%
7 138
 
2.4%
8 98
 
1.7%
9 69
 
1.2%
10 55
 
1.0%
ValueCountFrequency (%)
206 1
< 0.1%
199 1
< 0.1%
124 1
< 0.1%
97 1
< 0.1%
91 2
< 0.1%
86 1
< 0.1%
72 1
< 0.1%
62 2
< 0.1%
60 1
< 0.1%
57 1
< 0.1%

basket_size
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct2363
Distinct (%)41.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean260.60816
Minimum1
Maximum74215
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size89.0 KiB
2024-07-01T14:12:14.627243image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4
Q174.9375
median151.25
Q3289.27778
95-th percentile733.5625
Maximum74215
Range74214
Interquartile range (IQR)214.34028

Descriptive statistics

Standard deviation1073.9887
Coefficient of variation (CV)4.1210861
Kurtosis3960.3825
Mean260.60816
Median Absolute Deviation (MAD)96.25
Skewness58.354632
Sum1484163.5
Variance1153451.6
MonotonicityNot monotonic
2024-07-01T14:12:14.939915image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 115
 
2.0%
2 72
 
1.3%
3 51
 
0.9%
4 49
 
0.9%
5 35
 
0.6%
6 29
 
0.5%
12 26
 
0.5%
72 22
 
0.4%
100 22
 
0.4%
88 21
 
0.4%
Other values (2353) 5253
92.2%
ValueCountFrequency (%)
1 115
2.0%
2 72
1.3%
3 51
0.9%
3.333333333 1
 
< 0.1%
4 49
0.9%
5 35
 
0.6%
5.333333333 1
 
< 0.1%
5.666666667 1
 
< 0.1%
6 29
 
0.5%
6.142857143 1
 
< 0.1%
ValueCountFrequency (%)
74215 1
< 0.1%
14149 1
< 0.1%
13956 1
< 0.1%
7824 1
< 0.1%
6009.333333 1
< 0.1%
5963 1
< 0.1%
5197 1
< 0.1%
4300 1
< 0.1%
4282 1
< 0.1%
4280 1
< 0.1%

unique_basket_size
Real number (ℝ)

HIGH CORRELATION 

Distinct1262
Distinct (%)22.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean39.983069
Minimum1
Maximum1113
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size89.0 KiB
2024-07-01T14:12:15.264257image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1.3083333
Q19
median18
Q335.658333
95-th percentile175.3
Maximum1113
Range1112
Interquartile range (IQR)26.658333

Descriptive statistics

Standard deviation77.010961
Coefficient of variation (CV)1.9260893
Kurtosis32.300798
Mean39.983069
Median Absolute Deviation (MAD)11.333333
Skewness4.9960754
Sum227703.58
Variance5930.6881
MonotonicityNot monotonic
2024-07-01T14:12:15.569645image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 283
 
5.0%
2 160
 
2.8%
3 116
 
2.0%
13 108
 
1.9%
10 103
 
1.8%
9 99
 
1.7%
6 96
 
1.7%
4 93
 
1.6%
5 91
 
1.6%
11 91
 
1.6%
Other values (1252) 4455
78.2%
ValueCountFrequency (%)
1 283
5.0%
1.2 1
 
< 0.1%
1.25 1
 
< 0.1%
1.333333333 2
 
< 0.1%
1.5 7
 
0.1%
1.568181818 1
 
< 0.1%
1.571428571 1
 
< 0.1%
1.666666667 4
 
0.1%
1.833333333 1
 
< 0.1%
2 160
2.8%
ValueCountFrequency (%)
1113 1
< 0.1%
748 1
< 0.1%
730 1
< 0.1%
720 1
< 0.1%
704 1
< 0.1%
686 1
< 0.1%
675 1
< 0.1%
674 1
< 0.1%
661 1
< 0.1%
650 1
< 0.1%

avg_ticket
Real number (ℝ)

SKEWED 

Distinct5501
Distinct (%)96.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean44.751248
Minimum0.42
Maximum77183.6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size89.0 KiB
2024-07-01T14:12:15.892253image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0.42
5-th percentile3.4600235
Q17.95
median15.858824
Q321.984194
95-th percentile76.32
Maximum77183.6
Range77183.18
Interquartile range (IQR)14.034194

Descriptive statistics

Standard deviation1043.7985
Coefficient of variation (CV)23.324455
Kurtosis5245.7371
Mean44.751248
Median Absolute Deviation (MAD)7.5030735
Skewness71.303053
Sum254858.36
Variance1089515.3
MonotonicityNot monotonic
2024-07-01T14:12:16.221552image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.75 11
 
0.2%
4.95 10
 
0.2%
2.95 9
 
0.2%
1.25 9
 
0.2%
7.95 8
 
0.1%
12.75 7
 
0.1%
8.25 7
 
0.1%
1.65 7
 
0.1%
3.35 6
 
0.1%
5.95 6
 
0.1%
Other values (5491) 5615
98.6%
ValueCountFrequency (%)
0.42 3
0.1%
0.535 1
 
< 0.1%
0.65 1
 
< 0.1%
0.79 1
 
< 0.1%
0.8371428571 1
 
< 0.1%
0.84 2
< 0.1%
0.85 3
0.1%
1.002222222 1
 
< 0.1%
1.02 1
 
< 0.1%
1.03875 1
 
< 0.1%
ValueCountFrequency (%)
77183.6 1
< 0.1%
13305.5 1
< 0.1%
4453.43 1
< 0.1%
3861 1
< 0.1%
3202.92 1
< 0.1%
3096 1
< 0.1%
1687.2 1
< 0.1%
1377.077778 1
< 0.1%
1001.2 1
< 0.1%
952.9875 1
< 0.1%

frequency
Real number (ℝ)

HIGH CORRELATION 

Distinct1226
Distinct (%)21.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.54729349
Minimum0.0054495913
Maximum17
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size89.0 KiB
2024-07-01T14:12:16.559265image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0.0054495913
5-th percentile0.01104363
Q10.024926433
median1
Q31
95-th percentile1
Maximum17
Range16.99455
Interquartile range (IQR)0.97507357

Descriptive statistics

Standard deviation0.55026024
Coefficient of variation (CV)1.0054208
Kurtosis139.13414
Mean0.54729349
Median Absolute Deviation (MAD)0
Skewness4.8585728
Sum3116.8364
Variance0.30278633
MonotonicityNot monotonic
2024-07-01T14:12:16.879588image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 2879
50.6%
2 47
 
0.8%
0.0625 17
 
0.3%
0.02777777778 17
 
0.3%
0.02380952381 16
 
0.3%
0.08333333333 15
 
0.3%
0.09090909091 15
 
0.3%
0.03448275862 14
 
0.2%
0.02941176471 14
 
0.2%
0.07692307692 13
 
0.2%
Other values (1216) 2648
46.5%
ValueCountFrequency (%)
0.005449591281 1
 
< 0.1%
0.005464480874 1
 
< 0.1%
0.005479452055 1
 
< 0.1%
0.005494505495 1
 
< 0.1%
0.005586592179 2
< 0.1%
0.005602240896 1
 
< 0.1%
0.005617977528 2
< 0.1%
0.00566572238 1
 
< 0.1%
0.005681818182 2
< 0.1%
0.005698005698 3
0.1%
ValueCountFrequency (%)
17 1
 
< 0.1%
4 1
 
< 0.1%
3 5
 
0.1%
2 47
 
0.8%
1.142857143 1
 
< 0.1%
1 2879
50.6%
0.75 1
 
< 0.1%
0.6666666667 3
 
0.1%
0.550802139 1
 
< 0.1%
0.5335120643 1
 
< 0.1%

returned
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct214
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean31.268306
Minimum0
Maximum74215
Zeros4191
Zeros (%)73.6%
Negative0
Negative (%)0.0%
Memory size89.0 KiB
2024-07-01T14:12:17.236548image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile38.3
Maximum74215
Range74215
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1004.3217
Coefficient of variation (CV)32.11948
Kurtosis5232.3595
Mean31.268306
Median Absolute Deviation (MAD)0
Skewness71.057699
Sum178073
Variance1008662.1
MonotonicityNot monotonic
2024-07-01T14:12:17.553867image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 4191
73.6%
1 169
 
3.0%
2 150
 
2.6%
3 105
 
1.8%
4 89
 
1.6%
6 78
 
1.4%
5 61
 
1.1%
12 52
 
0.9%
7 44
 
0.8%
8 43
 
0.8%
Other values (204) 713
 
12.5%
ValueCountFrequency (%)
0 4191
73.6%
1 169
 
3.0%
2 150
 
2.6%
3 105
 
1.8%
4 89
 
1.6%
5 61
 
1.1%
6 78
 
1.4%
7 44
 
0.8%
8 43
 
0.8%
9 41
 
0.7%
ValueCountFrequency (%)
74215 1
< 0.1%
9014 1
< 0.1%
8004 1
< 0.1%
4427 1
< 0.1%
3768 1
< 0.1%
3332 1
< 0.1%
2878 1
< 0.1%
2022 1
< 0.1%
2012 1
< 0.1%
1776 1
< 0.1%

Interactions

2024-07-01T14:12:04.196661image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:11:28.790866image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:11:32.397276image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:11:36.035281image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:11:40.419473image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:11:43.678709image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:11:46.860672image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:11:49.837121image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:11:54.737638image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:11:57.946934image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:12:01.086241image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:12:04.476208image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:11:29.389212image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:11:32.654390image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:11:36.321934image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:11:40.820250image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:11:43.944481image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:11:47.121061image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:11:50.109267image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:11:55.122603image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:11:58.240632image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:12:01.363504image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:12:04.735870image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:11:29.862272image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:11:32.943754image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:11:36.589954image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:11:41.090237image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:11:44.232825image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:11:47.381487image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:11:50.383197image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:11:55.539231image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:11:58.505755image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:12:01.622225image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:12:05.003768image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:11:30.194130image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:11:33.233562image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:11:36.937143image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:11:41.382422image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:11:44.535280image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:11:47.658851image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:11:50.660989image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:11:55.815329image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:11:58.777760image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:12:01.898844image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:12:05.340146image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:11:30.471052image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:11:33.509740image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:11:37.375268image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:11:41.668090image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:11:44.837573image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:11:47.935109image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:11:51.005782image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:11:56.107639image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:11:59.092762image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:12:02.210078image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:12:05.639840image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:11:30.759115image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:11:33.796780image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:11:37.811598image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:11:41.954743image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:11:45.149213image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:11:48.235925image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:11:51.445341image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:11:56.378214image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:11:59.383623image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:12:02.507734image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:12:06.002425image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:11:30.997520image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:11:34.064686image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:11:38.229656image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:11:42.240781image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:11:45.437932image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:11:48.494463image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:11:51.868444image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:11:56.618119image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:11:59.644858image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:12:02.765287image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:12:06.453282image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:11:31.304068image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:11:34.359857image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:11:38.670999image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:11:42.525605image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:11:45.701857image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:11:48.762434image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:11:52.224060image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:11:56.891016image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:11:59.931828image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:12:03.077739image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:12:06.858397image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:11:31.556431image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:11:35.210933image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:11:39.076419image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:11:42.792644image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:11:45.966353image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:11:49.033448image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:11:53.483856image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:11:57.153375image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:12:00.235656image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:12:03.365167image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:12:07.304213image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:11:31.843022image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:11:35.481070image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:11:39.497421image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:11:43.093588image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:11:46.279388image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:11:49.303352image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:11:53.892423image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:11:57.425389image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:12:00.520453image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:12:03.649677image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:12:07.681265image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:11:32.132108image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:11:35.750249image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:11:39.956647image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:11:43.391735image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:11:46.564756image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:11:49.576497image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:11:54.312089image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:11:57.683747image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:12:00.799472image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-01T14:12:03.921670image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Correlations

2024-07-01T14:12:17.826722image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
avg_ticketbasket_sizecustomer_iddistinct_stock_codefrequencyrecencyreturnedrevenuetotal_productstotal_purchasesunique_basket_size
avg_ticket1.0000.266-0.386-0.140-0.228-0.1480.2680.3440.3300.267-0.354
basket_size0.2661.000-0.1470.612-0.129-0.1980.1820.7230.7900.1570.609
customer_id-0.386-0.1471.000-0.0480.3800.245-0.277-0.181-0.291-0.3830.113
distinct_stock_code-0.1400.612-0.0481.000-0.359-0.3790.3160.8360.7810.5330.768
frequency-0.228-0.1290.380-0.3591.0000.486-0.366-0.453-0.514-0.7990.031
recency-0.148-0.1980.245-0.3790.4861.000-0.320-0.426-0.496-0.597-0.038
returned0.2680.182-0.2770.316-0.366-0.3201.0000.4330.4560.538-0.022
revenue0.3440.723-0.1810.836-0.453-0.4260.4331.0000.9300.6440.488
total_products0.3300.790-0.2910.781-0.514-0.4960.4560.9301.0000.6940.412
total_purchases0.2670.157-0.3830.533-0.799-0.5970.5380.6440.6941.000-0.047
unique_basket_size-0.3540.6090.1130.7680.031-0.038-0.0220.4880.412-0.0471.000

Missing values

2024-07-01T14:12:08.262240image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
A simple visualization of nullity by column.
2024-07-01T14:12:09.192141image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

customer_idrevenuerecencytotal_productsdistinct_stock_codetotal_purchasesbasket_sizeunique_basket_sizeavg_ticketfrequencyreturned
0178505391.21372.01733.0297.034.050.9705888.73529418.15222217.00000040.0
1130473232.5956.01390.0171.09.0154.44444419.00000018.9040350.02830235.0
2125836705.382.05028.0232.015.0335.20000015.46666728.9025000.04032350.0
313748948.2595.0439.028.05.087.8000005.60000033.8660710.0179210.0
415100876.00333.080.03.03.026.6666671.000000292.0000000.07317122.0
5152914623.3025.02102.0102.014.0150.1428577.28571445.3264710.04011529.0
6146885630.877.03621.0327.021.0172.42857115.57142917.2197860.057221399.0
7178095411.9116.02057.061.012.0171.4166675.08333388.7198360.03352041.0
81531160767.900.038194.02379.091.0419.71428626.14285725.5434640.243316474.0
9160982005.6387.0613.067.07.087.5714299.57142929.9347760.0243900.0
customer_idrevenuerecencytotal_productsdistinct_stock_codetotal_purchasesbasket_sizeunique_basket_sizeavg_ticketfrequencyreturned
5776227004839.421.01074.062.01.01074.062.078.0551611.00.0
577713298360.001.096.02.01.096.02.0180.0000001.00.0
577814569227.391.079.012.01.079.012.018.9491671.00.0
57792270417.901.014.07.01.014.07.02.5571431.00.0
5780227053.351.02.02.01.02.02.01.6750001.00.0
5781227065699.001.01747.0634.01.01747.0634.08.9889591.00.0
5782227076756.060.02010.0730.01.02010.0730.09.2548771.00.0
5783227083217.200.0654.059.01.0654.059.054.5288141.00.0
5784227093950.720.0731.0217.01.0731.0217.018.2060831.00.0
578512713794.550.0505.037.01.0505.037.021.4743241.00.0